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Saharan Dust Composition on the Way to the Americas and Potential Impacts on Atmosphere and Biosphere

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Saharan Dust Composition on the Way to the Americas and Potential Impacts on Atmosphere and Biosphere 1 Saharan dust composition on the way to the Americas and potential impacts on atmosphere and biosphere K. Kandler Institut für Angewandte Geowissenschaften, Technische Universität Darmstadt, 64287 Darmstadt, Germany The Saharan dust plume 2 over the Western Atlantic Ocean K. Kandler: Zum Einfluss des SaharastaubsKarayampudi et auf al., 1999, das doi : Klima10.1175/1520 – -Erkenntnise0477(1999)080 aus dem Saharan Mineral Dust Experiment (SAMUM) The Saharan dust plume 3 on its arrival overover the the Caribbean Western Atlantic Ocean PR daily averaged surface dust concentration (in µg-3), modelled for 23 June 1993 Kallos et al. 2006, doi: 10.1029/2005JD006207 K. Kandler: Zum Einfluss des SaharastaubsKarayampudi et auf al., 1999, das doi : Klima10.1175/1520 – -Erkenntnise0477(1999)080 aus dem Saharan Mineral Dust Experiment (SAMUM) Case study of a dust event 4 from Bodélé depression reaching South America daily lidar scans starting Feb 19, 2008 from Ben-Ami et al. 2010 doi: 10.5194/acp-10-7533-2010 5 Dust composition and its dependencies, interaction and potential impacts DEPOSITION TRANSPORT EMISSION terrestrial solar radiative impact wet processing radiative impact photochemistry cloud impact indirect radiative impact anthropogeneous/ biomass burning aerosol admixture heterogeneous chemistry dry removal sea-salt interaction wet removal terrestrial geological basement ecosystem impact type of weathering surface transport human/plant/animal marine ecosystem impact health issues chemical processing emission meteorology 6 Implications for radiation transfer – dust radiative forcing Top-of the atmosphere (TOA) net 90% Clay 5% Quartz radiative forcing for different dust 5% Hematite mineralogical compositions(1) 75% Clays 20% Quartz 5% Hematite Shortwave forcing case study, including 80% Clays o measured aerosol size distribution o measured vertical aerosol distribution 20% Hematite o measured planetary surface albedo o measured particle shape cooling warming o derived particle refractive index -30 -20 -10 0 10 o derived particle single scattering albedo (2) (2) Planetary surface Top of the atmosphere cooling , W/m², , W/m², over ocean cooling effects effects warming radiative radiative radiative radiative Surface cooling over desert decrease in sea surface temperature change in tropical cyclone activity(3) aerosol aerosol 1data from Sokolik et al. 1999, doi: 10.1029/1998JD200048 2Otto et al. 2009, doi: 10.1111/j.1600-0889.2008.00389.x 3Evan et al. 2008, doi: 10.1029/2007GC001774 7 Implications for radiation transfer – dust composition and terrestrial radiation Thermal infrared radiative forcing for different dust compositions(2) ² 40 m Mass extinction efficiency for different minerals / W 30 in the atmospheric window wavelength region(1) , g n i 20 c r o f 10 A O T 0 ² m / 10 dust dust W storm , (Niger) x 20 u l f dust g 30 (Barbados) dust n Afghan Afghan i l SW USA SW USA l e 40 dust w n Negev Negev w 50 o Saharan d e 60 c a Saharan f r u 70 S 80 1Hansell et al. 2011, doi:10.5194/acp-11-1527-2011 2data from Sokolik et al. 1998, doi: 10.1029/98JD00049 8 Dust composition and clouds Modification by clouds . Uptake of gaseous precursor species via aqueous chemistry . Aqueous reaction with (acidic) species . Composition-selective removal by wet deposition . Internal mixing by droplet/particle scavenging or coalescence Impact on clouds . Fresh dust particles can act as cloud condensation nuclei (dependency on mineralogy)(1) . Dust particles as giant cloud condensation nuclei (GCCN) may alter precipitation(2) . Increase of ice nucleus (IN) concentrations, IN at higher temperatures(3) . Mineral dust contributes by 21 to 84% to the IN concentration(4) over the Amazon basin . In a case study, more than 79 % of cloud droplets at Cape Verde contained dust particles(5) . Water vapor competition of GCCN versus smaller dust particles makes precipitation impact depending on cloud conditions (i. e. liquid water content, but also gaseous chemistry)(6) impact is ambiguous, depending on cloud microstructure(7) . Short-lived convective clouds are most sensitive(6) . Indirect impact through change of atmospheric dynamics by radiative impact (surface cooling, increase in atmospheric stability)(6) 1Kumar et al. 2011, 10.5194/acp-11-3527-2011 2Yin et al. 2000, 10.1016/S0169-8095(99)00046-0 3Sassen et al. 2003, doi: 10.1029/2003GL017371 4Prenni et al. 2009, doi: 10.1038/NGEO517 5Twohy et al. 2009, doi: 10.1029/2008GL035846 6Rosenfeld et al. 2001, doi: 10.1073/pnas.101122798 7Seifert et al. 2011, doi: 10.5194/acpd-11-20203-2011 9 Dust and ecosystems Marine ecosystems . Fe (and possibly, P) can limit bio-productivity on Oceans directly or by co-limiting N fixation(1,2) . Saharan dust is made responsible for the degradation of coral reefs(3), but possible pathways are still explored(4) . Toxic red tides in the Gulf of Mexico need dust Fe (and maybe P) input to start(5) . On the nature (and impact) of P on marine ecosystems “remarkably little is known“(2) . P input by dust can increase bacterial activity in Mediterranean freshwater ecosystems(6) Terrestrial ecosystems . Forest ecosystems on extremely leached soils (like Amazonia) are short in nutrients (P, K) which can be provided by dust fall(7,8) . For example, half of the total inputs to soil-and-biomass P can be derived from dust in Puerto Rico’s Luquillo Mountains(9) . Forests on less leached soils can have deficit of Ca and K(10) . A tropical Andean forest in Ecuador receives considerable amounts of Ca and Mg from Saharan dust(11) 1Jickells et al. 2005, doi: 10.1126/science.1105959 2Okin et al. 2011, doi: 10.1029/2010GB003858 3Shinn et al. 2000, doi: 10.1029/2000GL011599 4Rypien 2008, doi: 10.3354/meps07600 5Walsh et al. 2006, doi: 10.1029/2004JC002813 6Reche et al. 2009, doi: 10.4319/lo.2009.54.3.0869 7Swap et al. 1992, doi: 10.1034/j.1600-0889.1992.t01-1-00005.x 8Okin et al. 2004, doi: 10.1029/2003GB002145 9Pett-Ridge 2009, doi: 10.1007/s10533-009-9308-x 10Bond 2010, doi: 10.1007/s11104-010-0440-0 11Boy et al. 2008, doi: 10.1029/2007GB002960 10 Emission stage – sources, composition, variation DEPOSITION TRANSPORT EMISSION terrestrial solar radiative impact wet processing radiative impact photochemistry cloud impact indirect radiative impact anthropogeneous/ biomass burning aerosol admixture heterogeneous chemistry dry removal sea-salt interaction wet removal terrestrial geological basement ecosystem impact type of weathering surface transport human/plant/animal marine ecosystem impact health issues chemical processing emission meteorology 11 Emission stage – general mineralogy . Dust composition is highly variably . Quartz and phyllosilicates are omnipresent . Phyllosilicates might be . (frequently reported) kaolinite, illite . (less frequently) chlorite, muscovite, montmorillionite, biotite, palygorskite, smectites and inter-stratified clay minerals . Mostly, additional silicates are reported . (frequently) albite, anorthite, K-feldspars . (less frequently) chrysotile, orthoclase . Calcite, dolomite and sometimes apatite are found in varying abundance . Hematite, goethite and sometimes ilmenite are the main iron compounds . Sulfates, nitrates and chlorides are usually not reported with their mineralogical denomination (some of them might [fractionally] recrystallize depending on environmental conditions) . In addition, a plethora of other mineral species are reported, including biological debris (diatomite), metal oxides (rutile, periclase, baddeleyite, spinel), iron-rich minerals (lepidocrocite, limonite), carbonates (aragonite, magnesite), sulfates (anhydrite, gypsum, thenardite, mirabilite, mascagnite, glauberite), silicates (chloritoid, leucite, forsterite, zircon, enstatite) and graphite 12 Emission stage – sources and composition 1.78-2.41Bu Composition of 0.74-2.97To1 Saharan dust and 2.11BL (SD) topsoils characterized by (Ca+Mg)/Fe ratio(1) 0.40-0.46Kr (SD) 2.30-2.53Av1 5.17GF Li Av2 3.77 0.62 2.08Av2 6.07Li (SD) 3.65Li Ca 3.56 1.16Av1 3.35-7.24Mo 4.29-8.40Ab GT 0.65Av2 0.71-1.19 CD 2.56 0.66Mo 0.61-0.84Av1 0.66Ca 0.88-2.12To2 0.62-0.85GT Br He 0.25-2.17 Mou 0.22 Mo 0.50 Li 0.45 Mou 0.53 Mo 0.63 0.37 Mou Sh Mo Ca 0.61 0.86-1.39 0.43 0.45 Mou 0.42Ca 0.74 0.40-0.65Or Ra Major source 0.83 0.23Mb 0.80-0.83Wi (Ca+Mg)/Fe regions compiled 0.42MW Wi dust 0.66-0.84 0.25 0.5 from different <0.25 1 - 2 2 - 4 >4 techniques are 0.04-0.21Ad - 0.5 - 1 identified(2) soil 1Scheuvens et al., in preparation for Earth. Sci. Reviews – details on original literature are given there 2Formenti et al. 2011, doi: 10.5194/acp-11-8231-2011 13 Mineralogical composition as function of source regions – an example dust intensity Quartz K-feldspar Plagioclase Calcite Illite (1M) I Kaolinite Smectites Chlorite Gypsum Halite Hematite K Rutile Mai13 Mai14 Mai15 Mai16 Mai17 Mai18 Mai19 Mai20 Mai21 Mai22 Mai23 Mai24 Mai25 Mai26 Mai27 Mai28 Mai29 Mai30 Mai31 Jun01 Jun02 Jun03 Jun04 Jun05 Jun06 dust phases by meteorology and satellite obs. DU1 DU2 DU3 Quartz K-feldspar Plagioclase Calcite Illite (1M) dominant Kaolinite major Smectites minor Chlorite traces Gypsum detected Halite not det. Hematite not invest. Rutile Jan14 Jan15 Jan16 Jan17 Jan18 Jan19 Jan20 Jan21 Jan22 Jan23 Jan24 Jan25 Jan26 Jan27 Jan28 Jan29 Jan30 Jan31 Feb 01Feb 02Feb 03Feb 04Feb 05Feb 06Feb 07Feb 08Feb 09Feb data from Kandler et al. 2009, doi: 10.1111/j.1600-0889.2008.00385.x and Kandler et al. 2011, doi: 10.1111/j.1600-0889.2011.00550.x 14 Change in mineralogical composition with particle size seen by chemical fingerprints 0.5 to < 1 µm 1 to < 2.5 µm 2.5 to < 10 µm 10 to < 25 µm 0.6 0.6 0.6 0.6 0.5 0.5 0.5 0.5 i 0.4 0.4 0.4 0.4 S / ) e F 0.3 0.3 0.3 0.3 + g M 0.2 0.2 0.2 0.2 ( 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 0.6 0.6 0.6 0.6 0.5 0.5 0.5 0.5 i S / ) 0.4 0.4 0.4 0.4 a C + 0.3 0.3 0.3 0.3 K + a 0.2 0.2 0.2 0.2 N ( 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Al/Si Al/Si Al/Si Al/Si 0.03 0.01 0.003 0.001 0.0003 0.0001 data from Kandler et al.
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